f3c77b1750
- Implemented the WiFi DensePose model in PyTorch, including CSI phase processing, modality translation, and DensePose prediction heads. - Added a comprehensive training utility for the model, including loss functions and training steps. - Created a CSV file to document hardware specifications, architecture details, training parameters, performance metrics, and advantages of the model.
23 lines
530 B
Python
23 lines
530 B
Python
# Install PyTorch and other dependencies
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import subprocess
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import sys
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def install_package(package):
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subprocess.check_call([sys.executable, "-m", "pip", "install", package])
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try:
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import torch
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print("PyTorch already installed")
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except ImportError:
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print("Installing PyTorch...")
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install_package("torch")
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install_package("torchvision")
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try:
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import numpy
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print("NumPy already installed")
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except ImportError:
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print("Installing NumPy...")
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install_package("numpy")
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print("All packages ready!") |